Modern cybersecurity platforms are highly fragmented. In a given network environment, one application may be implemented to protect email communications, another may analyze potentially malicious files, another may perform behavioral analysis of user actions, another may scrutinize incoming or outgoing network traffic, and another may protect a DevOps code pipeline. Many enterprises have many more security applications running in their environment, each performing a single dedicated task or a handful or related tasks.
In addition to the administrative and overhead burdens involved in decentralized cybersecurity protection, security problems may arise. For example, when two or more security applications reach conflicting decisions about how to handle a particular action (e.g., downloading a file, writing data to a server, creating a new cloud computing account, accessing a secure database, etc.), insecurities may occur. If one security application determines that the action should be permitted, and another decides to block it, there is no decision-making as to which of the conflicting decisions should override the other. Similarly, even if two security applications are identical in terms of their functionality, they may deviate from each other in terms of timing. If one security application calls for an action to be performed at a particular time (e.g., based on a particular time zone), and another security application calls for the action to be performed at a different time (e.g., based on a different time zone), conflicts may also arise in the operation of the respective security applications.
These types of conflicts among applications lead to both false positives and false negatives. If the security measure an organization should implement (e.g., denying access) is overridden by an unsound or erroneous measure (e.g., granting access), the result may be a security vulnerability where the organization becomes compromised to attacks. Conversely, if proper decisions to grant access are overridden by unsound or erroneous decisions to block access, workflows may be disrupted and negative impacts will occur n terms of network uptime and productivity.
As cyberattacks increase in their complexity, the move toward fragmented and highly specialized cybersecurity platforms is likely to continue. No single platform will be able to protect against varying attacks occurring in new and different ways. The result of this is likely to be an increase in conflicts between cybersecurity platforms. No solutions exist for identifying these conflicts among disparate cybersecurity platforms and addressing them in an efficient and security-oriented manner.
Accordingly, in view of these and other deficiencies in existing techniques for addressing inconsistencies among varying cybersecurity platforms, technological improvements are needed for automatically identifying such inconsistencies. Techniques should allow for automatic remediation of inconsistencies in a secure manner, and/or prompts for security administrators to resolve such inconsistencies.